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Software Engineer Data Infrastructure Jobs in California

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Software Engineer Data Infrastructure information

See California salary details

$43.9K

$128K

$175.2K

How much do software engineer data infrastructure jobs pay per year?

As of Jun 10, 2026, the average yearly pay for software engineer data infrastructure in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

How does a Software Engineer in Data Infrastructure typically collaborate with data scientists and other engineering teams?

As a Software Engineer in Data Infrastructure, you'll frequently work alongside data scientists, analysts, and other engineering teams to ensure that data pipelines and storage systems are reliable, scalable, and efficient. Collaboration often involves translating data requirements into technical solutions, troubleshooting data flow issues, and optimizing infrastructure for both performance and cost. Regular meetings, code reviews, and cross-functional planning sessions are common, allowing you to gain insights from various perspectives and ensure the infrastructure meets the evolving needs of the organization.

What is the difference between Software Engineer Data Infrastructure vs Data Engineer?

AspectSoftware Engineer Data InfrastructureData Engineer
Required CredentialsBachelor's in CS or related, often with certifications in cloud or data toolsBachelor's in CS, Data Science, or related; similar certifications
Work EnvironmentDevelops and maintains data infrastructure, collaborates with data teamsBuilds data pipelines, manages data storage and processing systems
Employer & Industry UsageTech companies, data-driven organizations, cloud providersFinance, healthcare, tech firms, any industry with large data needs
Common Search & ComparisonYesYes

Software Engineer Data Infrastructure and Data Engineer roles often overlap in skills and work environment, focusing on building and maintaining data systems. However, Software Engineers Data Infrastructure tend to focus more on the underlying infrastructure and integration, while Data Engineers emphasize data pipeline development and data management. Both roles are essential in data-driven organizations and require similar credentials and industry usage.

What are Software Engineer Data Infrastructure?

Software Engineer Data Infrastructure are professionals who design, build, and maintain the underlying systems and tools that enable organizations to collect, store, process, and analyze large volumes of data efficiently. They work on creating scalable data pipelines, managing databases, and ensuring data reliability and security. Their work supports data scientists, analysts, and business teams by providing robust, high-performance infrastructure for all data-related operations.

What are the key skills and qualifications needed to thrive as a Software Engineer Data Infrastructure, and why are they important?

To thrive as a Software Engineer Data Infrastructure, you need strong programming skills (such as Python, Java, or Scala), a solid understanding of distributed systems, and experience with data modeling and storage solutions, often backed by a degree in computer science or a related field. Familiarity with technologies like Hadoop, Spark, Kafka, SQL/NoSQL databases, and cloud platforms, as well as certifications in cloud or big data, are highly valued. Excellent problem-solving abilities, collaboration, and clear communication distinguish top performers in this role. These skills ensure robust, scalable, and reliable data infrastructure that supports organizational analytics and business goals.
What are popular job titles related to Software Engineer Data Infrastructure jobs in California? For Software Engineer Data Infrastructure jobs in California, the most frequently searched job titles are:
What job categories do people searching Software Engineer Data Infrastructure jobs in California look for? The top searched job categories for Software Engineer Data Infrastructure jobs in California are:
Software Engineer Data Infrastructure jobs near you
Infographic showing various Software Engineer Data Infrastructure job openings in California as of June 2026, with employment types broken down into 94% Full Time, 1% Temporary, and 5% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

Software Engineer, Data Infrastructure

Thinking Machines Lab

San Francisco, CA • On-site

$350K - $475K/yr

Full-time

Medical, Dental, Vision, PTO

Posted 29 days ago

Job description

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals.
We are scientists, engineers, and builders who've created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything.
About the Role
We're looking for an engineer to join us and contribute to data infrastructure. You'll join a small, high-impact team responsible for architecting and scaling the core infrastructure behind distributed training pipelines, multimodal data catalogs, and intelligent processing systems that operate over petabytes of data.
Infrastructure is critical to us: it's the bedrock that enables every breakthrough. You'll work directly with researchers to accelerate experiments, develop new datasets, improve infrastructure efficiency, and enable key insights across our data assets.
If you're excited by distributed systems, large-scale data mining, open-source tools like Spark, Kafka, Beam, Ray, and Delta Lake, and enjoy building from the ground up, we'd love to hear from you.
Note: This is an "evergreen role" that we keep open on an on-going basis to express interest. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role.
What You'll Do
  • Design, build, and operate scalable, fault-tolerant infrastructure for LLM Research: distributed compute, data orchestration, and storage across modalities.
  • Develop high-throughput systems for data ingestion, processing, and transformation - including training data catalogs, deduplication, quality checks, and search.
  • Build systems for traceability, reproducibility, and robust quality control at every stage of the data lifecycle.
  • Implement and maintain monitoring and alerting to support platform reliability and performance.
  • Collaborate with research teams to unlock new features, improve data quality, and accelerate training cycles.
Skills and Qualifications
Minimum qualifications:
  • Bachelor's degree or equivalent experience in computer science, engineering, or similar.
  • Proficiency in at least one backend language (we use Python or Rust).
  • Are fluent in distributed compute frameworks such as Apache Spark or Ray.
  • Are deeply familiar with cloud infrastructure, data lake architectures, and batch and streaming pipelines.
  • Comfort operating across the stack and owning projects end-to-end.
  • Thrive in a highly collaborative environment involving many, different cross-functional partners and subject matter experts.
  • A bias for action with a mindset to take initiative to work across different stacks and different teams where you spot the opportunity to make sure something ships.

Preferred qualifications - we encourage you to apply if you meet some but not all of these:
  • Have hands-on experience with Kafka, dbt, Terraform, and Airflow.
  • Have experience building a web crawler.
  • Have extensive experience understanding and scaling deduplication, data mining, and search.
  • Have strong knowledge of file formats and storage systems (e.g., Parquet, Delta Lake, etc.) and how they impact performance and scalability.
  • Are proactive about documentation, testing, and empowering your teammates with good tooling.
Logistics
  • Location: This role is based in San Francisco, California.
  • Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD.
  • Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together.
  • Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed.

As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.
Thinking Machines Lab will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the California Fair Chance Act, the San Francisco Fair Chance Ordinance, and any other applicable state or local fair chance ordinance or law.

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